This paper describes the standardization of the proton-induced x-ray emission（PIXE） technique for finding the elemental composition of thick samples. For the standardization, three different samples of standard refe...This paper describes the standardization of the proton-induced x-ray emission（PIXE） technique for finding the elemental composition of thick samples. For the standardization, three different samples of standard reference materials（SRMs） were analyzed using this technique and the data were compared with the already known data of these certified SRMs. These samples were selected in order to cover the maximum range of elements in the periodic table. Each sample was irradiated for three different values of collected beam charges at three different times. A proton beam of 2.57 Me V obtained using 5UDH-II Pelletron accelerator was used for excitation of x-rays from the sample. The acquired experimental data were analyzed using the GUPIXWIN software. The results show that the SRM data and the data obtained using the PIXE technique are in good agreement.展开更多
A program for quantitative PIXE analysis of thick sample (TSPIXE) without reference material has been developed at Fudan University. Our program can be applied to the energy range of 10 keV to 10 MeV and is suitable f...A program for quantitative PIXE analysis of thick sample (TSPIXE) without reference material has been developed at Fudan University. Our program can be applied to the energy range of 10 keV to 10 MeV and is suitable for the analysis of all elements with 11 【 Z 【 92. NBS reference materials were analyzed to provide the experimental test of TSPIXE program.展开更多
提出了一种基于稳定竞争自适应重加权采样(stability competitive adaptive reweighted sampling,SCARS)的无标模型传递方法。利用有用信息标准即稳定度指数(定义为回归系数除以其标准偏差的绝对值)和传递后的预测均方根误差(root mean ...提出了一种基于稳定竞争自适应重加权采样(stability competitive adaptive reweighted sampling,SCARS)的无标模型传递方法。利用有用信息标准即稳定度指数(定义为回归系数除以其标准偏差的绝对值)和传递后的预测均方根误差(root mean squared error of prediction,RMSEP),选择重要的、受测样参数影响不敏感的波长变量,能够消除或减少不同仪器或测量条件对样本信息反应差异,提高模型传递效果。此外,在该方法中,光谱变量被压缩、降维,从而使模型传递更稳定。采用该方法对谷物的近红外光谱分析模型在不同仪器之间进行传递研究。结果表明,该方法能消除仪器间的大部分差异,较好地实现模型传递效果。与正交信号校正法(orthogonal signal correction,OSC)、蒙特卡罗结合无用信息变量消除法(Monte Carlo uninformative variable elimination,MCUVE)、竞争自适应重加权采样法(competitive adaptive reweighted sampling,CARS)的比较表明,SCARS不仅在传递精度上能取得比OSC、MCUVE及CARS更好的效果,而且能有效地对光谱数据进行压缩,简化并优化传递过程。展开更多
文摘This paper describes the standardization of the proton-induced x-ray emission（PIXE） technique for finding the elemental composition of thick samples. For the standardization, three different samples of standard reference materials（SRMs） were analyzed using this technique and the data were compared with the already known data of these certified SRMs. These samples were selected in order to cover the maximum range of elements in the periodic table. Each sample was irradiated for three different values of collected beam charges at three different times. A proton beam of 2.57 Me V obtained using 5UDH-II Pelletron accelerator was used for excitation of x-rays from the sample. The acquired experimental data were analyzed using the GUPIXWIN software. The results show that the SRM data and the data obtained using the PIXE technique are in good agreement.
基金The Project Supported by National Natural Science Foundation of China
文摘A program for quantitative PIXE analysis of thick sample (TSPIXE) without reference material has been developed at Fudan University. Our program can be applied to the energy range of 10 keV to 10 MeV and is suitable for the analysis of all elements with 11 【 Z 【 92. NBS reference materials were analyzed to provide the experimental test of TSPIXE program.
文摘提出了一种基于稳定竞争自适应重加权采样(stability competitive adaptive reweighted sampling,SCARS)的无标模型传递方法。利用有用信息标准即稳定度指数(定义为回归系数除以其标准偏差的绝对值)和传递后的预测均方根误差(root mean squared error of prediction,RMSEP),选择重要的、受测样参数影响不敏感的波长变量,能够消除或减少不同仪器或测量条件对样本信息反应差异,提高模型传递效果。此外,在该方法中,光谱变量被压缩、降维,从而使模型传递更稳定。采用该方法对谷物的近红外光谱分析模型在不同仪器之间进行传递研究。结果表明,该方法能消除仪器间的大部分差异,较好地实现模型传递效果。与正交信号校正法(orthogonal signal correction,OSC)、蒙特卡罗结合无用信息变量消除法(Monte Carlo uninformative variable elimination,MCUVE)、竞争自适应重加权采样法(competitive adaptive reweighted sampling,CARS)的比较表明,SCARS不仅在传递精度上能取得比OSC、MCUVE及CARS更好的效果,而且能有效地对光谱数据进行压缩,简化并优化传递过程。
